An exploration of the literature on the use of 'swarm intelligence-based techniques' for public service problems

The importance of studying public service systems and finding robust solutions to the problems encountered in public service management has increased considerably over the past decade. One of the main objectives is to find acceptable solutions to Public Service Problems (PSPs) within an affordable period of time. However, many PSPs remain difficult to solve within a reasonable time due to their complexity and dynamic nature. This requires solving PSPs with techniques which provide efficient algorithmic solutions. There has been increasing attention in the literature to solving PSPs through the use of Swarm Intelligence-Based Techniques (SIBTs) like ant colony optimisation, particle swarm optimisation, Bee(s) Algorithm (BA), etc. This paper presents a review of Swarm Intelligence (SI) applications in public services (including PSPs in specific application areas), as well as the models and SI algorithms that have been reported in the literature. [Received 30 January 2008; Revised 4 December 2008; Revised 17 March 2009; Accepted 23 March 2009]

[1]  D. Pham,et al.  THE BEES ALGORITHM, A NOVEL TOOL FOR COMPLEX OPTIMISATION PROBLEMS , 2006 .

[2]  S. Favuzza,et al.  Optimal Electrical Distribution Systems Reinforcement Planning Using Gas Micro Turbines by Dynamic Ant Colony Search Algorithm , 2007, IEEE Transactions on Power Systems.

[3]  Ben Paechter,et al.  A Comparison of the Performance of Different Metaheuristics on the Timetabling Problem , 2002, PATAT.

[4]  C.E. Zoumas,et al.  Comparison of two metaheuristics with mathematical programming methods for the solution of OPF , 2005, Proceedings of the 13th International Conference on, Intelligent Systems Application to Power Systems.

[5]  Angus R. Simpson,et al.  Ant Colony Optimization for Design of Water Distribution Systems , 2003 .

[6]  F. Dyer The biology of the dance language. , 2002, Annual review of entomology.

[7]  Xu Gang,et al.  Max-min ant colony optimization for design of water distribution system , 2006 .

[8]  Malcolm Yoke-Hean Low,et al.  A Bee Colony Optimization Algorithm to Job Shop Scheduling , 2006, Proceedings of the 2006 Winter Simulation Conference.

[9]  Panta Lucic,et al.  Modeling Transportation Problems Using Concepts of Swarm Intelligence and Soft Computing , 2002 .

[10]  Karl O. Jones,et al.  Comparison of bees algorithm, ant colony optimisation and particle swarm optimisation for PID controller tuning , 2008, CompSysTech.

[11]  Léon J. M. Rothkrantz,et al.  Ant Based Mechanism for Crisis Response Coordination , 2006, ANTS Workshop.

[12]  Zahra Naji Azimi,et al.  Hybrid heuristics for Examination Timetabling problem , 2005, Appl. Math. Comput..

[13]  Suet Yee Chu Particle swarm optimization , 2009 .

[14]  Scutchfield,et al.  Public health services and systems research. , 2012, American journal of preventive medicine.

[15]  Duc Truong Pham,et al.  OPTIMIZATION OF THE WEIGHTS OF MULTI-LAYERED PERCEPTIONS USING THE BEES ALGORITHM , 2006 .

[16]  M. Dorigo,et al.  Aco Algorithms for the Traveling Salesman Problem , 1999 .

[17]  Tracy Sock Yin Tai,et al.  SEARCH AND OPTIMISATION WITH SMART ANT-LIKE SOFTWARE AGENTS , 1970 .

[18]  Toshiyuki Nakagaki,et al.  Physarum solver: A biologically inspired method of road-network navigation , 2006 .

[19]  Christian Blum,et al.  Ant colony optimization: Introduction and recent trends , 2005 .

[20]  Bassem Jarboui,et al.  A combinatorial particle swarm optimization for solving multi-mode resource-constrained project scheduling problems , 2008, Appl. Math. Comput..

[21]  Alice E. Smith,et al.  AN ANT COLONY APPROACH TO THE ORIENTEERING PROBLEM , 2006 .

[22]  Guo-Chang Gu,et al.  Research on particle swarm optimization: a review , 2004, Proceedings of 2004 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.04EX826).

[23]  Dušan Teodorović,et al.  Swarm intelligence systems for transportation engineering: Principles and applications , 2008 .

[24]  Ann E. Marucheck,et al.  Service Management - Academic Issues and Scholarly Reflections from Operations Management Researchers , 2007, Decis. Sci..

[25]  Barry J. Adams,et al.  Honey-bee mating optimization (HBMO) algorithm for optimal reservoir operation , 2007, J. Frankl. Inst..

[26]  Patrick R. McMullen,et al.  Ant colony optimization techniques for the vehicle routing problem , 2004, Adv. Eng. Informatics.

[27]  Lionel Amodeo,et al.  Optimization of natural gas pipeline transportation using ant colony optimization , 2009, Comput. Oper. Res..

[28]  Eleonora Riva Sanseverino,et al.  Adaptive and Dynamic Ant Colony Search Algorithm for Optimal Distribution Systems Reinforcement Strategy , 2006, Applied Intelligence.

[29]  Xudong Wang,et al.  Urban Traffic Flow Forecasting Model of Double RBF Neural Network Based on PSO , 2006, Sixth International Conference on Intelligent Systems Design and Applications.

[30]  K. Frisch The dance language and orientation of bees , 1967 .

[31]  W. Kurutach,et al.  Feeder-switch relocation for value-based distribution reliability assessment , 2004, 2004 IEEE International Engineering Management Conference (IEEE Cat. No.04CH37574).

[32]  Michael Eley,et al.  Ant Algorithms for the Exam Timetabling Problem , 2006, PATAT.

[33]  T. Seeley,et al.  Group decision making in honey bee swarms , 2006 .

[34]  Riccardo Poli,et al.  Particle Swarm Optimisation , 2011 .

[35]  M. Sivajothi,et al.  An Ant Colony Based Protocol to Support Multimedia Communication in Ad Hoc Wireless Networks , 2008, 2008 International Conference on Security Technology.

[36]  Angus R. Simpson,et al.  Ant colony optimization for power plant maintenance scheduling optimization—a five-station hydropower system , 2008, Ann. Oper. Res..

[37]  Alice E. Smith,et al.  A genetic algorithm for the orienteering problem , 2000, Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512).

[38]  Salman Mohagheghi,et al.  Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems , 2008, IEEE Transactions on Evolutionary Computation.

[39]  A. Chebouba,et al.  New Method to Minimize Fuel Consumption of Gas Pipeline Using Ant Colony Optimization Algorithms , 2006, 2006 International Conference on Service Systems and Service Management.

[40]  H. Abbass,et al.  Multi-objective Ant Colony Optimization for Weather Avoidance in a Free Flight Environment , 2006 .

[41]  Mouloud Koudil,et al.  Using artificial bees to solve partitioning and scheduling problems in codesign , 2007, Appl. Math. Comput..

[42]  Yangsheng Xu,et al.  Optimal Design for Urban Mass Transit Network Based on Evolutionary Algorithms , 2005, ICNC.

[43]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[44]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[45]  Marco Wiering,et al.  Multiple Ant Colony Systems for the Busstop Allocation Problem , 2001 .

[46]  Dušan Teodorović,et al.  Mitigating Traffic Congestion: Solving the Ride-Matching Problem by Bee Colony Optimization , 2008 .

[47]  Xin-She Yang,et al.  Engineering Optimizations via Nature-Inspired Virtual Bee Algorithms , 2005, IWINAC.

[48]  D.T. Pham,et al.  Application of the Bees Algorithm to the Training of Learning Vector Quantisation Networks for Control Chart Pattern Recognition , 2006, 2006 2nd International Conference on Information & Communication Technologies.

[49]  Marco Dorigo,et al.  The ant colony optimization meta-heuristic , 1999 .

[50]  Michael Sampels,et al.  Ant Algorithms for the University Course Timetabling Problem with Regard to the State-of-the-Art , 2003, EvoWorkshops.

[51]  Andreas T. Ernst,et al.  Staff scheduling and rostering: A review of applications, methods and models , 2004, Eur. J. Oper. Res..

[52]  N. P. Padhy,et al.  Application of particle swarm optimization technique and its variants to generation expansion planning problem , 2004 .

[53]  Luca Maria Gambardella,et al.  Ant Algorithms for Discrete Optimization , 1999, Artificial Life.

[54]  Javier Jaén Martínez,et al.  A grid ant colony algorithm for the orienteering problem , 2005, 2005 IEEE Congress on Evolutionary Computation.

[55]  Chuntian Cheng,et al.  A Parallel Ant Colony Algorithm for Bus Network Optimization , 2007, Comput. Aided Civ. Infrastructure Eng..

[56]  Katerina Papatzelou,et al.  Optimal solid waste collection routes identified by the ant colony system algorithm , 2007, Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA.

[57]  M. A. Abido,et al.  Optimal power flow using particle swarm optimization , 2002 .

[58]  Stephen Robinson,et al.  The application of optimal foraging theory in route finding algorithms for ad-hoc networks , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[59]  Dong Hwa Kim,et al.  A hybrid genetic algorithm and bacterial foraging approach for global optimization , 2007, Inf. Sci..

[60]  林我聰 The Historical Review and Current Trends in Swarm Intelligence by Bibilometric Approach , 2007 .

[61]  Massimo Paolucci,et al.  A new discrete particle swarm optimization approach for the single-machine total weighted tardiness scheduling problem with sequence-dependent setup times , 2009, Eur. J. Oper. Res..

[62]  T. Stützle,et al.  A Review on the Ant Colony Optimization Metaheuristic: Basis, Models and New Trends , 2002 .

[63]  Petros Koumoutsakos,et al.  Optimization based on bacterial chemotaxis , 2002, IEEE Trans. Evol. Comput..

[64]  Krishna C. Jha,et al.  Exact and Heuristic Methods for the Weapon Target Assignment Problem , 2003 .

[65]  Luca Maria Gambardella,et al.  Ant colony system: a cooperative learning approach to the traveling salesman problem , 1997, IEEE Trans. Evol. Comput..

[66]  Zwe-Lee Gaing,et al.  Particle swarm optimization to solving the economic dispatch considering the generator constraints , 2003 .

[67]  S. Kannan,et al.  Application and comparison of metaheuristic techniques to generation expansion planning problem , 2005, IEEE Transactions on Power Systems.

[68]  H. Yoshida,et al.  A particle swarm optimization for reactive power and voltage control considering voltage security assessment , 1999, 2001 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.01CH37194).

[69]  Hideki Katagiri,et al.  An Application of Interactive Fuzzy Satisficing Approach with Particle Swarm Optimization for Multiobjective Emergency Facility Location Problem with A-distance , 2007, 2007 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making.

[70]  K. Passino,et al.  Biomimicry of Social Foraging Bacteria for Distributed Optimization: Models, Principles, and Emergent Behaviors , 2002 .

[71]  Duc Truong Pham,et al.  PRELIMINARY DESIGN USING THE BEES ALGORITHM , 2007 .

[72]  Ant Colony Optimization-Scholarpedia , 2007 .

[73]  B. Bullnheimer,et al.  A NEW RANK BASED VERSION OF THE ANT SYSTEM: A COMPUTATIONAL STUDY , 1997 .

[74]  Riccardo Poli,et al.  Analysis of the publications on the applications of particle swarm optimisation , 2008 .

[75]  Mauro Dell'Orco,et al.  Multi Agent Systems Approach to Parking Facilities Management , 2005 .

[76]  Marco Tomassini,et al.  Fuzzy Evolutionary Algorithms , 2001 .

[77]  Eleonora Riva Sanseverino,et al.  Ant Colony Search Algorithm for Optimal Strategical Planning of Electrical Distribution Systems Expansion , 2005, Applied Intelligence.

[78]  Marco Dorigo Ant colony optimization , 2004, Scholarpedia.

[79]  G. Beni,et al.  The concept of cellular robotic system , 1988, Proceedings IEEE International Symposium on Intelligent Control 1988.

[80]  Yoshikazu Fukuyama,et al.  A hybrid particle swarm optimization for distribution state estimation , 2003, 2003 IEEE Power Engineering Society General Meeting (IEEE Cat. No.03CH37491).

[81]  Gang Liu Improvement of Government Organization Service Management , 2006, 2006 IEEE International Conference on Service Operations and Logistics, and Informatics.

[82]  L.N. de Castro Immune, swarm, and evolutionary algorithms. Part I: basic models , 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..

[83]  D. Karaboga,et al.  On the performance of artificial bee colony (ABC) algorithm , 2008, Appl. Soft Comput..

[84]  Dušan Teodorović,et al.  Bee Colony Optimization – a Cooperative Learning Approach to Complex Transportation Problems , 2005 .

[85]  R.G. Harley,et al.  Swarm Intelligence for Transmission System Control , 2007, 2007 IEEE Power Engineering Society General Meeting.

[86]  Chou-Yuan Lee,et al.  An immunity-based ant colony optimization algorithm for solving weapon-target assignment problem , 2002, Appl. Soft Comput..

[87]  Peter A. Lindsay,et al.  Mapping lessons from ants to free flight: an ant-based weather avoidance algorithm in free flight airspace , 2006, SPIE Micro + Nano Materials, Devices, and Applications.

[88]  Jianming Hu Study on the optimization methods of transit network based on Ant Algorithm , 2001, IVEC2001. Proceedings of the IEEE International Vehicle Electronics Conference 2001. IVEC 2001 (Cat. No.01EX522).

[89]  J. Deneubourg,et al.  The self-organizing exploratory pattern of the argentine ant , 1990, Journal of Insect Behavior.

[90]  Marco Dorigo,et al.  The hyper-cube framework for ant colony optimization , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[91]  Craig Tovey,et al.  From honeybees to Internet servers: biomimicry for distributed management of Internet hosting centers , 2007, Bioinspiration & biomimetics.

[92]  Angus R. Simpson,et al.  Ant colony optimization for power plant maintenance scheduling optimization , 2005, GECCO '05.

[93]  Graham Kendall,et al.  Optimisation in a road traffic system using collaborative search , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[94]  Ali Maroosi,et al.  Application of honey-bee mating optimization algorithm on clustering , 2007, Appl. Math. Comput..

[95]  M Reyes Sierra,et al.  Multi-Objective Particle Swarm Optimizers: A Survey of the State-of-the-Art , 2006 .

[96]  Andries Petrus Engelbrecht,et al.  Fundamentals of Computational Swarm Intelligence , 2005 .

[97]  Sung Hoon Jung,et al.  Queen-bee evolution for genetic algorithms , 2003 .

[98]  J. Bishop Stochastic searching networks , 1989 .

[99]  M. Dorigo,et al.  1 Positive Feedback as a Search Strategy , 1991 .

[100]  M. Muoz,et al.  Self–Adaptive Bacteria Swarm for Optimization , 2008, 2008 Electronics, Robotics and Automotive Mechanics Conference (CERMA '08).

[101]  Yuanhai Li,et al.  Optimal groundwater monitoring design using an ant colony optimization paradigm , 2007, Environ. Model. Softw..

[102]  S. Le Hegarat-Mascle,et al.  Swarm intelligence in optimisation problems , 2003 .

[103]  Chukwudi Anyakoha,et al.  A review of particle swarm optimization. Part II: hybridisation, combinatorial, multicriteria and constrained optimization, and indicative applications , 2008, Natural Computing.

[104]  Christine Solnon,et al.  Ants can solve constraint satisfaction problems , 2002, IEEE Trans. Evol. Comput..

[105]  B. Mozafari,et al.  An Approach for Under Voltage Load Shedding Using Particle Swarm Optimization , 2006, 2006 IEEE International Symposium on Industrial Electronics.

[106]  Angus R. Simpson,et al.  Application of two ant colony optimisation algorithms to water distribution system optimisation , 2006, Math. Comput. Model..

[107]  J.G. Vlachogiannis,et al.  Optimization of Power Systems based on Ant Colony System Algorithms: An Overview , 2005, Proceedings of the 13th International Conference on, Intelligent Systems Application to Power Systems.

[108]  Marco Dorigo,et al.  Swarm intelligence: from natural to artificial systems , 1999 .

[109]  H. L. Ong,et al.  Solving the feeder bus network design problem by genetic algorithms and ant colony optimization , 2006, Adv. Eng. Softw..

[110]  P. Bedi,et al.  Avoiding Traffic Jam Using Ant Colony Optimization - A Novel Approach , 2007, International Conference on Computational Intelligence and Multimedia Applications (ICCIMA 2007).

[111]  Yutian Liu,et al.  Reactive power optimization based on PSO in a practical power system , 2004, IEEE Power Engineering Society General Meeting, 2004..

[112]  Chuntian Cheng,et al.  A Dynamic Task Scheduling Approach Based on Wasp Algorithm in Grid Environment , 2005, ICNC.

[113]  Yanli Yang,et al.  Integrated Routing Wasp Algorithm and Scheduling Wasp Algorithm for Job Shop Dynamic Scheduling , 2008, 2008 International Symposium on Electronic Commerce and Security.

[114]  H. Ishii,et al.  An emergency service facility location problem with fuzzy objective and constraint , 1992, [1992 Proceedings] IEEE International Conference on Fuzzy Systems.

[116]  Thomas Stützle,et al.  Ant Colony Optimization , 2009, EMO.

[117]  Mauro Birattari,et al.  Swarm Intelligence , 2012, Lecture Notes in Computer Science.

[118]  Kevin M. Passino,et al.  Distributed optimization and control using only a germ of intelligence , 2000, Proceedings of the 2000 IEEE International Symposium on Intelligent Control. Held jointly with the 8th IEEE Mediterranean Conference on Control and Automation (Cat. No.00CH37147).

[119]  Cezar Augusto Sierakowski,et al.  A software tool for teaching of particle swarm optimization fundamentals , 2008, Adv. Eng. Softw..

[120]  Yutian Liu,et al.  An adaptive PSO algorithm for reactive power optimization , 2003 .

[121]  M. R. AlRashidi,et al.  A Survey of Particle Swarm Optimization Applications in Power System Operations , 2006 .

[122]  Chukwudi Anyakoha,et al.  A review of particle swarm optimization. Part I: background and development , 2007, Natural Computing.

[123]  An-Pin Chen,et al.  A new efficient approach for data clustering in electronic library using ant colony clustering algorithm , 2006, Electron. Libr..

[124]  Zhigang Liu,et al.  Regional Bus Timetabling Model with Synchronization , 2007 .

[125]  Paul P. Maglio,et al.  Service systems, service scientists, SSME, and innovation , 2006, CACM.

[126]  J. M. Bishop,et al.  Anarchic techniques for pattern classification , 1989 .

[127]  Shu-Chuan Chu,et al.  Timetable Scheduling Using Particle Swarm Optimization , 2006, First International Conference on Innovative Computing, Information and Control - Volume I (ICICIC'06).

[128]  Jen-yu Huang Using Ant Colony Optimization to Solve Train Timetabling Problem of Mass Rapid Transit , 2006, JCIS.

[129]  F. Azuaje Artificial Immune Systems: A New Computational Intelligence Approach , 2003 .

[130]  Marco Dorigo,et al.  Ant colony optimization for continuous domains , 2008, Eur. J. Oper. Res..

[131]  Kevin M. Passino,et al.  Bacterial Foraging Optimization , 2010, Int. J. Swarm Intell. Res..

[132]  KarabogaDervis,et al.  A powerful and efficient algorithm for numerical function optimization , 2007 .

[133]  Chunming Yang,et al.  A new particle swarm optimization technique , 2005, 18th International Conference on Systems Engineering (ICSEng'05).

[134]  Lale Özbakır,et al.  Artificial Bee Colony Algorithm and Its Application to Generalized Assignment Problem , 2007 .

[135]  Michael Sampels,et al.  A MAX-MIN Ant System for the University Course Timetabling Problem , 2002, Ant Algorithms.

[136]  S. Su,et al.  A genetic algorithm with domain knowledge for weapon‐target assignment problems , 2002 .

[137]  Isamu Watanabe An ACO algorithm for service restoration in power distribution systems , 2005, 2005 IEEE Congress on Evolutionary Computation.

[138]  D. Hall,et al.  Water as a public service , 2006 .

[139]  Omid Bozorg Haddad,et al.  Honey-Bees Mating Optimization (HBMO) Algorithm: A New Heuristic Approach for Water Resources Optimization , 2006 .

[140]  Q.Y. Jiang,et al.  A queen-bee evolution based on genetic algorithm for economic power dispatch , 2004, 39th International Universities Power Engineering Conference, 2004. UPEC 2004..

[141]  Thomas Stützle,et al.  MAX-MIN Ant System , 2000, Future Gener. Comput. Syst..

[142]  Mouloud Koudil,et al.  Using Bees to Solve a Data-Mining Problem Expressed as a Max-Sat One , 2005, IWINAC.

[143]  H.M. Khodr,et al.  Ant colony system algorithm for the planning of primary distribution circuits , 2004, IEEE Transactions on Power Systems.

[144]  T. Seeley The Wisdom of the Hive , 1995 .

[145]  G.K. Venayagamoorthy,et al.  Optimal control parameters for a UPFC in a multimachine using PSO , 2005, Proceedings of the 13th International Conference on, Intelligent Systems Application to Power Systems.

[146]  Pisal Yenradee,et al.  PSO-based algorithm for home care worker scheduling in the UK , 2007, Comput. Ind. Eng..

[147]  Dervis Karaboga,et al.  A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm , 2007, J. Glob. Optim..

[148]  Seyed Hossein Hosseinian,et al.  A novel approach for optimal chiller loading using particle swarm optimization , 2008 .

[149]  Walter J. Gutjahr,et al.  An ACO algorithm for a dynamic regional nurse-scheduling problem in Austria , 2007, Comput. Oper. Res..

[150]  T. Besley,et al.  INCENTIVES, CHOICE, AND ACCOUNTABILITY IN THE PROVISION OF PUBLIC SERVICES , 2003 .

[151]  Dušan Teodorović,et al.  Schedule synchronization in public transit using the fuzzy ant system , 2005 .